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Large Grain Size Stochastic Optimization Alignment

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Permanent URL	http://hdl.lib.byu.edu/1877/2579
Title	Large Grain Size Stochastic Optimization Alignment
BYU Creator	Carroll, Hyrum Clement, Mark J. Ridge, Perry Sneddon, Dan Snell, Quinn O.
Keywords	DNA sequencing; phylogenetic search
Description/Abstract	DNA sequence alignment is a critical step in identifying homology between organisms. The most widely used alignment program, ClustalW, is known to suffer from the local minima problem, where suboptimal guide trees produce incorrect gap insertions. The optimization alignment approach, has been shown to be effective in combining alignment and phylogenetic search in order to avoid the problems associated with poor guide trees. The optimization alignment algorithm operates at a small grain size, aligning each tree found, wasting time producing multiple sequence alignments for suboptimal trees. This research develops and analyzes a large grain size algorithm for optimization alignment that iterates through steps of alignment and phylogeny search, thus improving the quality of guide trees used for computation of multiple sequence alignments and eliminating computation of multiple sequence alignments for sub-optimal guide trees. Local minima are avoided by the use of stochastic search methods. Large Grain Size Stochastic Optimization Alignment (LGA) exploits the relationship between phylogenies and multiple sequence alignments, and in so doing achieves improved alignment accuracy. LGA is licensed under the GNU General Public License. Source code and data sets are publicly available at http://csl.cs.byu.edu/lga/.
Source	"Large Grain Size Stochastic Optimization Alignment", Perry Ridge, Hyrum Carroll, Dan Sneddon, Mark Clement, Quinn Snell, IEEE Symposium on BioInformatics and BioEngineering (BIBE), Arlington, Virginia, October 2006, pp 127.;
Publisher	IEEE
Date Original	2006-10
Date Digital	2010-10-14
Language	English eng en
Publication Type	Articles
Type	Text
Format	application/pdf
Owning Institution	Brigham Young University
BYU College	College of Physical and Mathematical Sciences
BYU Department	Computer Science
Copyright Status	(c) 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.;
Copyright Use Information	http://www.lib.byu.edu/generic_copyright.html

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